Validation Of Computational Models Research Articles

LPBF Processability of NiTiHf Alloys: Systematic Modeling and Single-Track Studies.

Research into the processability of NiTiHf high-temperature shape memory alloys (HTSMAs) via laser powder bed fusion (LPBF) is limited; nevertheless, these alloys show promise for applications in extreme environments. This study aims to address this limitation by investigating the printability of four NiTiHf alloys with varying Hf content (1, 2, 15, and 20 at. %) to assess their suitability for LPBF applications. Solidification cracking is one of the main limiting factors in LPBF processes, which occurs during the final stage of solidification. To investigate the effect of alloy composition on printability, this study focuses on this defect via a combination of computational modeling and experimental validation. To this end, solidification cracking susceptibility is calculated as Kou's index and Scheil-Gulliver model, implemented in Thermo-Calc/2022a software. An innovative powder-free experimental method through laser remelting was conducted on bare NiTiHf ingots to validate the parameter impacts of the LPBF process. The result is the processability window with no cracking likelihood under diverse LPBF conditions, including laser power and scan speed. This comprehensive investigation enhances our understanding of the processability challenges and opportunities for NiTiHf HTSMAs in advanced engineering applications.

Fluid Dynamics Effects of a Porous Blockage on Laminar Flow in the Interior Subchannels of a 61-Pin Wire-Wrapped Rod Bundle

Flow blockages in Liquid Metal Fast Reactor (LMFR) fuel assemblies that can cause fuel pin cladding failures require further investigation for the development and optimization of these Generation IV reactor designs. The objective of this study was to experimentally evaluate the effects of a porous blockage accident scenario on laminar flow behavior in the interior subchannels of a prototypical 61-pin wire-wrapped rod bundle. The laminar flow condition is considered because of its importance to natural circulation and loss-of-coolant-accident operating scenarios as well as the limited availability of experimental data. The matched-index-of-refraction method was utilized to obtain two-dimension two-component time-resolved particle image velocimetry (TR-PIV) measurements at three planes centered on blocked and neighboring subchannel regions. Time-averaged first-order and second-order statistics, computed by Reynolds decomposition, were visualized including the mean and fluctuating streamwise and spanwise velocity components. Line profiles described the evolution of flow from upstream regions, to separated flow, and recombination downstream, while a modified Galilean decomposition distinguished differences between flow in the blocked measurement plane and flow in its neighboring counterpart region. Spatial-temporal cross-correlations were performed for the streamwise velocity fluctuations to characterize the convection velocity and decay of traveling vortices in the wake of the porous blockage. The isothermal TR-PIV measurements from this study provide high-fidelity experimental data sets for the validation of computational models and numerical studies to characterize complex fluid phenomena in wire-wrapped rod bundles during the potential accident scenario of a porous, interior flow blockage.

Development and Experimental Validation of a Two-stage Thermoelectric Heat Pump Computational Model for Heating Applications

The utilisation of thermoelectric technology as a heat pump in heating applications necessitates comprehensive investigation. The scalable nature of thermoelectric technology enables its operation at elevated temperatures without the requirement of refrigerants. In this work, an accurate computational model that can simulate one- and two-stage thermoelectric heat pumps is developed. This model uses the electric-thermal analogy and the finite difference method, including the thermoelectric effects, temperature dependent properties, thermal contact resistances and all heat exchangers, even the intermediate heat exchanger in the case of a two-stage configuration. Moreover, the model has been experimentally validated by built and tested prototypes, being the first time that a two-stage thermoelectric heat pump model is experimentally validated.The discrepancy between the simulated and experimental results is below the ± 10 % for COP, ± 8 % for generated heat and temperature lift in the airflow, and less than the ± 6 % for consumed power. Additonally, the model simulates real tendencies under different operating conditions, proving the reliability of the developed thermoelectric heat pump model.Finally, the model is used to optimise a thermoelectric system combining one- and two-stage thermoelectric heat pumps, and hybridising them with electric resistances. An airflow of 16.5 m3/h is heated from 25 °C to 160 °C, achieving a maximum COPtot of 1.21. Lastly, the importance of considering the thermal resistances of the heat exchangers is computationally modelled and demonstrated. Not taking them into account would overestimate the performance of the TEHP system by more than the 7 %.

Hydrodynamic Performance Assessment of Emerged, Alternatively Submerged and Submerged Semicircular Breakwater: An Experimental and Computational Study

Coastal protection structures are essential defenses against wave energy, safeguarding coastal communities. This study aims to refine coastal protection strategies by employing a semicircular breakwater (SBW) model. Through a combination of physical and computational models, the hydrodynamic properties of the SBW under regular wave conditions were thoroughly examined. The primary objectives included delineating the hydrodynamic characteristics of SBWs, developing a computational model to validate experimental findings. Hydrodynamic characteristics of the SBW model were scrutinized across various wave conditions. Experimental testing in a wave flume covered a range of relative water depths (d/h) from 0.667 to 1.667, wave steepness (Hi/L) spanning 0.02 to 0.06 and wave periods ranging from 0.8 to 2.5 s. Notably, analysis of an emerged SBW with d/h = 0.667 revealed superior wave reflection, while an alternative submerged SBW with d/h = 1.000 showed the highest energy loss. These findings are further corroborated by the validation of computational models against experimental outcomes for d/h = 0.667, 1.000, 1.333 and 1.667. Moreover, the investigation of forces revealed an inverse correlation between horizontal forces and wave height, while vertical forces showed nuanced variations, including a slightly decreasing average vertical force with greater relative wave period (B/L) for different immersion scenarios.

Decreased cellular excitability of pyramidal tract neurons in primary motor cortex leads to paradoxically increased network activity in simulated parkinsonian motor cortex.

Decreased excitability of pyramidal tract neurons in layer 5B (PT5B) of primary motor cortex (M1) has recently been shown in a dopamine-depleted mouse model of parkinsonism. We hypothesized that decreased PT5B neuron excitability would substantially disrupt oscillatory and non-oscillatory firing patterns of neurons in layer 5 (L5) of primary motor cortex (M1). To test this hypothesis, we performed computer simulations using a previously validated computer model of mouse M1. Inclusion of the experimentally identified parkinsonism-associated decrease of PT5B excitability into our computational model produced a paradoxical increase in rest-state PT5B firing rate, as well as an increase in beta-band oscillatory power in local field potential (LFP). In the movement-state, PT5B population firing and LFP showed reduced beta and increased high-beta, low-gamma activity of 20-35 Hz in the parkinsonian, but not in control condition. The appearance of beta-band oscillations in parkinsonism would be expected to disrupt normal M1 motor output and contribute to motor activity deficits seen in patients with Parkinson's disease (PD).

Experimental validation of a UAS at engine ingestion conditions: Part I Experiments

In recent years, uncrewed aircraft systems (UASs) have greatly increased in popularity and accessibility to the public. This dramatic increase has led to a substantial risk of a midair collision between a UAS and a commercial aircraft, and these collisions need to be analyzed to understand the dangers associated with them. Soft body (i.e., birds or ice) impacts have been happening since the early days of flight and have been studied thoroughly. In contrast, there has been significantly less research on hard body impacts, with most of the currently published research not using experimentally validated models at the conditions expected to be seen in an engine ingestion. The purpose of this work is to discuss the design and execution of experiments to improve and validate a UAS model for high speed impacts for future engine ingestion studies. The overall effort consisted of first conducting physical tests that represent specific high speed ingestion scenarios. Then simulating these tests using a high fidelity finite element tool. Then finally updating the model as necessary. The design of the experiments, experimental test setup, instrumentation and experimental results are highlighted in Part I of this work. The computational model update and validation of the UAS at conditions seen in an engine ingestion are done in Part II of this work.

Challenges and directions for digital twin implementation in otorhinolaryngology.

Digital twin technology heralds a transformative era in Otorhinolaryngology (ORL), merging the physical and digital worlds to offer dynamic, virtual models of physical entities or processes. These models, capable of simulating, predicting, and optimizing real-world counterparts, are evolving from static replicas to intelligent, adaptive systems. Fueled by advancements in communication, sensor technology, big data analytics, Internet of Things (IoT), and simulation technologies, artificial intelligence (AI), digital twins in ORL promise personalized treatment planning, virtual experimentation, and therapeutic intervention optimization. Despite their potential, the integration of digital twins in ORL faces challenges including data privacy and security, data integration and interoperability, computational demands, model validation and accuracy, ethical and regulatory considerations, patient engagement, and cost and accessibility issues. Overcoming these challenges requires robust data protection measures, seamless data integration, substantial computational resources, rigorous validation studies, ethical transparency, patient education, and making the technology accessible and affordable. Looking ahead, the future of digital twins in ORL is bright, with advancements in AI and machine learning, omics data integration, real-time monitoring, virtual clinical trials, patient empowerment, seamless healthcare integration, longitudinal data analysis, and collaborative research. These developments promise to refine diagnostic and treatment strategies, enhance patient care, and facilitate more efficient and tailored ORL research, ultimately leading to more effective and personalized ORL management.

Integrated computational modeling and in-silico validation of flavonoids-Alliuocide G and Alliuocide A as therapeutic agents for their multi-target potential: Combination of molecular docking, MM-GBSA, ADMET and DFT analysis

Alliuocide class of compounds belong to flavonoids and were isolated from Allium cepa. Alliuocide are the key phytoconstituents of Allium cepa having biological activities like anticancer, antidiabetic, anti-allergic, metabolic, and inflammatory disorders, antibacterial as well as effective antioxidants against chronic diseases. However, after their isolation report, there was no further work done and a gap of about 10 years. Herein, the present study was carried out to cover the gap and to identify new lead candidates in drug discovery pipeline. Alliuocide A and G were screened against various antioxidant, antidiabetic, anticancer and antibacterial target proteins. Target based screening by molecular docking against different target receptor co-crystal structure revealed Alliuocide A as potential hit, these results were further demonstrated by MM-GBSA studies. Further optimization of both compounds was done by in silico absorption, distribution, metabolism, excretion and toxicity (ADMET) studies. Both compounds followed Lipinski's rule of five therefore safe for further in vivo studies. Finally spectral studies along with quantum descriptors were carried out by employing DFT method at 6–311 G (d,p) basis set. These quantum chemical parameters proved to be important mechanism for correlating the inhibition efficiency with molecular quatum parameters. All these studies help in designing of derivatives for better pharmacological potential.

Scaling methodologies and similarity analysis for thermal hydraulics test facility development for water-cooled small modular reactor

Small modular reactors (SMRs) represent a promising option for providing clean and sustainable energy due to their potential for enhanced safety, reduced capital costs, and increased siting flexibility. However, new reactor systems require the development and operation of representative scaled-down test facilities to support the verification and validation of system computer codes and models. This study reviews the research on scaling methodologies and similarity principles pivotal in developing non-nuclear integral effects test and separate effects test facilities for water-cooled SMRs. The study focuses on a review of the scaling methods, similarity approaches, and possible challenges posed by the unique and compact design features of integral-pressurized water reactor-type SMRs, and their representative test facilities. This study also reviews previous research related to scaling and similarity methodologies and provides insights into design considerations for achieving prototypic conditions in test facilities. The findings and recommendations emphasize the broader impact of appropriate scaling and similarity principles to ensure meaningful and transferable results from non-nuclear test facilities to accelerate the safe and efficient deployment of next-generation water-cooled SMRs.

Prediction of BLEVE loading on structures

In a previous study by the authors, rigid structure assumption, as commonly used in analysing blast wave interaction with structures, was adapted in investigating the Boiling Liquid Expanding Vapour Explosion (BLEVE) pressure wave interaction with structures to predict BLEVE loads on structures. However, real structures are not rigid and the duration of BLEVE wave is much longer than that from high explosives and may be in the order of structural natural vibration period. Neglecting structural deformation, therefore, may lead to inaccurate predictions of BLEVE loads acting on the structure because structural deformation during the action of BLEVE wave would change the wave and the structure interaction. In this study, intensive numerical simulations are carried out using a validated computer model to investigate the influences of structural stiffness and BLEVE wave duration on the reflected BLEVE pressure on the structure. Based on the numerical results, prediction charts are proposed as a function of the BLEVE wave duration and structural fundamental vibration period for reliable predictions of BLEVE loads on structures. The findings of this study can be used to predict explosion loads in structural design against BLEVE.

Regional differences in stomach stretch during organ filling and their implications on the mechanical stress response

As part of the digestive system, the stomach plays a crucial role in the health and well-being of an organism. It produces acids and performs contractions that initiate the digestive process and begin the break-up of ingested food. Therefore, its mechanical properties are of interest. This study includes a detailed investigation of strains in the porcine stomach wall during passive organ filling. In addition, the observed strains were applied to tissue samples subjected to biaxial tensile tests. The results show inhomogeneous strains during filling, which tend to be higher in the circumferential direction (antrum: 13.2%, corpus: 22.0%, fundus: 67.8%), compared to the longitudinal direction (antrum: 4.8%, corpus: 24.7%, fundus: 50.0%) at a maximum filling of 3500 ml. Consequently, the fundus region experienced the greatest strain. In the biaxial tensile experiments, the corpus region appeared to be the stiffest, reaching nominal stress values above 400 kPa in the circumferential direction, whereas the other regions only reached stress levels of below 50 kPa in both directions for the investigated stretch range. Our findings gain new insight into stomach mechanics and provide valuable data for the development and validation of computational stomach models.

Modeling of Magnetic Films: A Scientific Perspective.

Magnetic thin-film modeling stands as a dynamic nexus of scientific inquiry and technological advancement, poised at the vanguard of materials science exploration. Leveraging a diverse suite of computational methodologies, including Monte Carlo simulations and molecular dynamics, researchers meticulously dissect the intricate interplay governing magnetism and thin-film growth across heterogeneous substrates. Recent strides, notably in multiscale modeling and machine learning paradigms, have engendered a paradigm shift in predictive capabilities, facilitating a nuanced understanding of thin-film dynamics spanning disparate spatiotemporal regimes. This interdisciplinary synergy, complemented by avantgarde experimental modalities such as in situ microscopy, promises a tapestry of transformative advancements in magnetic materials with far-reaching implications across multifaceted domains including magnetic data storage, spintronics, and magnetic sensing technologies. The confluence of computational modeling and experimental validation heralds a new era of scientific rigor, affording unparalleled insights into the real-time dynamics of magnetic films and bolstering the fidelity of predictive models. As researchers chart an ambitiously uncharted trajectory, the burgeoning realm of magnetic thin-film modeling burgeons with promise, poised to unlock novel paradigms in materials science and engineering. Through this intricate nexus of theoretical elucidation and empirical validation, magnetic thin-film modeling heralds a future replete with innovation, catalyzing a renaissance in technological possibilities across diverse industrial landscapes.

Mechanisms of coronary sinus reducer for treatment of myocardial ischemia: in silico study.

The coronary sinus reducer (CSR) is an emerging medical device for treating patients with refractory angina, often associated with myocardial ischemia. Patients implanted with CSR have shown positive outcomes, but the underlying mechanisms are unclear. This study sought to understand the mechanisms of CSR by investigating its effects on coronary microcirculation hemodynamics that may help explain the therapy's efficacy. We applied a validated computer model of the coronary microcirculation to investigate how CSR affects hemodynamics under different degrees of coronary artery stenosis. With moderate coronary stenosis, an increase in capillary transit time (CTT) [up to 69% with near-complete coronary sinus (CS) occlusion] is the key change associated with CSR. Because capillaries in the microcirculation can still receive oxygenated blood from the upstream artery with moderate stenosis, the increase in CTT allows more time for the exchange of gases and nutrients, aiding tissue oxygenation. With severe coronary stenosis; however, the redistribution of blood draining from the nonischemic region to the ischemic region (up to 96% with near-complete CS occlusion) and the reduction in capillary flow heterogeneity are the key changes associated with CSR. Because blood draining from the nonischemic region is not completely devoid of O2, the redistribution of blood to the capillaries in the ischemic region by CSR is beneficial especially when little or no oxygenated blood reaches these capillaries. This simulation study provides insights into the mechanisms of CSR in improving clinical symptoms. The mechanisms differ with the severity of the upstream stenosis.NEW & NOTEWORTHY Emerging coronary venous retroperfusion treatments, particularly coronary sinus reducer (CSR) for refractory angina linked to myocardial ischemia, show promise; however, their mechanisms of action are not well understood. We find that CSR's effectiveness varies with the severity of coronary stenosis. In moderate stenosis, CSR improves tissue oxygenation by increasing capillary transit time, whereas in severe stenosis, it redistributes blood from nonischemic to ischemic regions and reduces capillary flow heterogeneity.

Increased deadwood carbon stocks through planted forestry practices: insights from a Forest Inventory Survey in Japan

Deadwood, a vital component of forest ecosystems, constitutes a quintessential carbon reservoir that must be disclosed under the United Nations Framework Convention on Climate Change. This reservoir, comprising fallen logs, snags, and stumps, markedly affects carbon dynamics over decades. In this study, deadwood carbon stocks were quantified using data from 2674 sites in Japan surveyed between 2011 and 2015 via the National Forest Soil Carbon Inventory, and the deadwood carbon attributes in the country were explored. Deadwood were surveyed using the line intersect method for fallen logs and the belt transect method for stumps and snags. In Japan, the deadwood carbon stock (measured in t-C/ha) was quantified at 7.5 ± 9.74 (mean ± SD), with fallen logs at 3.26 ± 4.43, stumps at 2.45 ± 5.69, and snags at 1.80 ± 5.27, with significant differences detected among these stocks (p < .001). Considering deadwood carbon accumulation in Japan, planted forests exhibited a significantly larger (p < .001) deadwood carbon stock than natural forests. Moreover, planted forests exhibited a higher proportion of fallen logs than snags and stumps, indicating the effects associated with logs left on forest floors after thinning. Based on these findings, deadwood carbon stocks have the potential to bolster the validation and refinement of computational models used in carbon accounting.

Validation of computational fluid dynamics models for airway deposition with SPECT data of the same population

This study compared computational fluid dynamic (CFD) model predictions on aerosol deposition in six asthmatic patients to the in-vivo results of the same group. Patient-specific ventilation and internal air distribution were prescribed using inspiratory and expiratory CT scans of each patient, accounting for individual lobar air flow distribution. Moreover, the significant influence of realistic mouth and throat geometries on regional deposition is demonstrated. The in-vivo data were obtained from single photon emission computed tomography (SPECT) in 6 subjects with mild asthma selected from a database of historical clinical trials. The governing flow and particle tracking equations were solved numerically using a commercial CFD tool, and the modeled deposition results were compared to the SPECT data. Good agreement was found between the CFD model, applying k-ω SST turbulence model, and SPECT in terms of aerosol deposition. The average difference for the lobar deposition obtained from CFD model and SPECT/CT data was 2.1%. The high level of agreement is due to applying patient specific airway geometries and inspiratory/expiratory CT images, anatomical upper airways, and realistic airway trees. The results of this study show that CFD is a powerful tool to simulate patient-specific deposition if correct boundary conditions are applied and can generate similar information obtained with functional imaging tools, such as SPECT.

Numerical simulation prediction of critical heat flux for 5 × 5 rod bundle with multiple grid spacers and different cladding materials

The critical heat flux (CHF) is one of the safety standards for core thermal design and is crucial for the normal operation of the reactor. The CHF problem of rod bundles with grid spacers is a hot topic in related research. The successful design of grid spacers can improve channel CHF by affecting the flow of downstream coolant, and this detection analysis can be achieved through numerical simulation methods. In addition, most simulation studies have not considered the solid region of the cladding, so there is little research on the effect of cladding materials on CHF. The role of grid spacers in rod bundle CHF is the focus of this paper, and the influence of cladding materials is another discussion direction. In this paper, following meticulous mesh generation and computational model validation, a study on the CHF of the 5 × 5 rod bundle with multiple grid spacers and different cladding materials is carried out by using CFD software. The verification results indicated that the physical model established in this study can reasonably predict the generation location and critical power value in the 5 × 5 rod bundle with grid spacers. Furthermore, the study identified that the grid spacer exerts a significant influence on coolant flow within the channel, while the weakening of the mixing effect of the grid spacer on the coolant flow is the main factor to lead the boiling crisis upstream of the grid spacer. By comparing the effects of thermal properties of different materials on CHF, it was found that when the thermal conductivity ratio of the two materials is 1.08, CHF is almost identical under the condition of a reference heat flux of 0.1 MW/m2 as a step size. In addition to thermal properties, further attention may be paid to the influence of surface characteristics of materials on CHF in future work.

Development and Validation of Computational Fluid Dynamics Model of Ladle Furnace with Electromagnetic Stirring System.

Numerical methods are crucial to supporting the development of new technology in different industries, especially steelmaking, where many phenomena cannot be directly measured or observed under industrial conditions. As a result, further designing and optimizing steelmaking equipment and technology are not easy tasks. At the same time, numerical approaches enable modeling of various phenomena controlling material behavior and, thus, understanding the physics behind the processes occurring in different metallurgical devices. With this, it is possible to design and develop new technological solutions that improve the quality of steel products and minimize the negative impact on the environment. However, the usage of numerical approaches without proper validation can lead to misleading results and conclusions. Therefore, in this paper, the authors focus on the development of the CFD-based (computational fluid dynamics) approach to investigate the liquid steel flow inside one metallurgical device, namely a ladle furnace combined with an EMS (electromagnetic stirring) system. First, a numerical simulation of electromagnetic stirring in a scaled mercury model of a ladle furnace was carried out. The numerical results, such as stirring speed and turbulent kinetic energy, were compared with measurements in the mercury model. It was found that the results of the transient multiphase CFD model achieve good agreement with the measurements, but a free surface should be included in the CFD model to simulate the instability of the flow pattern in the mercury model. Based on the developed model, a full-scale industrial ladle furnace with electromagnetic stirring was also simulated and presented. This research confirms that such a coupled model can be used to design new types of EMS devices that improve molten steel flow in metallurgical equipment.

Digital empowerment and win-win co-operation for green and low-carbon industrial development: Analysis of regional differences based on GMM-ANN intelligence models

The study employs two sophisticated computational model validation mechanisms, Artificial Neural Network (ANN) and System Generalized Method of Moments (SYS-GMM), as the theoretical foundation for sustainable development theory. Within this research framework, ANN serves as an intelligent model for autonomously learning input data features by capturing the nonlinear and dynamic relationships within the data. This study thoroughly simulates and analyzes the intricate relationship between digital empowerment and win-win cooperation in green and low-carbon industrial development. The findings indicate a regional decreasing trend in digital empowerment in China, with percentages of 87.39%, 79.05%, and 65.85%, respectively. These regional variations may result from policy, economic structure, and social factors. Notably, a significant trend of win-win cooperation exists between digital empowerment and green low-carbon initiatives. This discovery implies that promoting digital empowerment contributes to reducing green carbon emissions, offering empirical evidence for the positive impact of digital technology on promoting environmental sustainability. This study unveils the empirical trend of digitally-enabled green, low-carbon industry development within the win-win cooperation framework and presents specific recommendations for future sustainability strategies. In addition to offering a scientific foundation for policymakers, this study provides a forward-looking perspective for academics engaged in the study of digital transformation and environmental sustainability. Through a comprehensive analysis of the intricate relationship between digital empowerment and win-win cooperation in the context of green and low-carbon industrial development, this study offers a profound understanding of the application of digital technology in sustainable development across diverse regions, contributing empirical research findings to advance sustainable development in China.

Non-invasive Estimation of Pressure Drop Across Aortic Coarctations: Validation of 0D and 3D Computational Models with In Vivo Measurements.

Blood pressure gradient ( ) across an aortic coarctation (CoA) is an important measurement to diagnose CoA severity and gauge treatment efficacy. Invasive cardiac catheterization is currently the gold-standard method for measuring blood pressure. The objective of this study was to evaluate the accuracy of estimates derived non-invasively using patient-specific 0D and 3D deformable wall simulations. Medical imaging and routine clinical measurements were used to create patient-specific models of patients with CoA (N = 17). 0D simulations were performed first and used to tune boundary conditions and initialize 3D simulations. across the CoA estimated using both 0D and 3D simulations were compared to invasive catheter-based pressure measurements for validation. The 0D simulations were extremely efficient ( 15 s computation time) compared to 3D simulations ( 30 h computation time on a cluster). However, the 0D estimates, unsurprisingly, had larger mean errors when compared to catheterization than 3D estimates (12.1 ± 9.9 mmHg vs 5.3 ± 5.4 mmHg). In particular, the 0D model performance degraded in cases where the CoA was adjacent to a bifurcation. The 0D model classified patients with severe CoA requiring intervention (defined as 20 mmHg) with 76% accuracy and 3D simulations improved this to 88%. Overall, a combined approach, using 0D models to efficiently tune and launch 3D models, offers the best combination of speed and accuracy for non-invasive classification of CoA severity.

Phase Composition and Phase Transformation of Additively Manufactured Nickel Alloy 718 AM Bench Artifacts

Additive manufacturing (AM) technologies offer unprecedented design flexibility but are limited by a lack of understanding of the material microstructure formed under their extreme and transient processing conditions and its subsequent transformation during post-build processing. As part of the 2022 AM Bench Challenge, sponsored by the National Institute of Standards and Technology, this study focuses on the phase composition and phase evolution of AM nickel alloy 718, a nickel-based superalloy, to provide benchmark data essential for the validation of computational models for microstructural predictions. We employed high-energy synchrotron X-ray diffraction, in situ synchrotron X-ray scattering, as well as high-resolution transmission electron microscopy for our analyses. The study uncovers critical aspects of the microstructure in its as-built state, its transformation during homogenization, and its phase evolution during subsequent aging heat treatment. Specifically, we identified secondary phases, monitored the dissolution and coarsening of microstructural elements, and observed the formation and stability of γ’ and γ” phases. The results provide the rigorous benchmark data required to understand the atomic and microstructural transformations of AM nickel alloy 718, thereby enhancing the reliability and applicability of AM models for predicting phase evolution and mechanical properties.